Picking the right artificial intelligence and machine learning book depends on your current knowledge and what you want to ...

The job title Quant is ubiquitously used. That makes it a dynamic, exciting and dynamic discipline, but one which also can ...

Ask the publishers to restore access to 500,000+ books. An icon used to represent a menu that can be toggled by interacting with this icon. ... Introduction to linear algebra by Lang, Serge, 1927-2005 ...

In this work, the effect of the stretch Weissenberg number, WiR, on the monomeric friction coefficient is investigated for three entangled linear isotactic polypropylenes (L-PP) and three entangled ...

python java clojure scala spark hadoop gpu intellij linear-algebra artificial-intelligence deeplearning neural-nets dl4j matrix-library deeplearning4j Updated Jun 4, 2025 Java ...

At present, Symmetric Positive Definite (SPD) matrix data is the most common non-Euclidean data in machine learning. Because SPD data don’t form a linear space, most machine learning algorithms can ...

The objectives of this work were to predict soil properties using pXRF data, comparing stepwise multiple linear regression (SMLR) and random forest (RF) methods, as well as mapping and validating soil ...

Resource demands prediction has become a promising tool to facilitate automatic scaling of resource management, which makes it feasible to reduce the cost and improve resource utilization in the cloud ...